This document presents the analyses done on the fish trait matrix.
DATRAS CGFS
Sources: - our own work on fishbase and IUCN - Beuhkof et al Pangea database and - benthos : xxx
## nbid nbNA
## Species 84 0
## habitat 6 0
## feeding.mode 4 0
## tl 71 0
## age.maturity 37 2
## growth.coefficient 77 0
## length.max 65 0
## age.max 37 0
## IUCN.status 6 0
##
## iter imp variable
## 1 1 age.maturity
## 2 1 age.maturity
## 3 1 age.maturity
## 4 1 age.maturity
## 5 1 age.maturity
## nbid nbNA
## Species 84 0
## habitat 6 0
## feeding.mode 4 0
## tl 71 0
## age.maturity 36 0
## growth.coefficient 77 0
## length.max 65 0
## age.max 37 0
## IUCN.status 6 0
## [1] 0 1 2 3 4 5
## [1] 0 2 3 4 5 14
## [1] 0.0 0.1 0.2 0.3 0.4 0.5 2.0
## [1] 0 50 100 200
## [1] 0 5 10 20 60
## nbid nbNA
## Species 84 0
## habitat 6 0
## feeding.mode 4 0
## tl 3 0
## age.maturity 5 0
## growth.coefficient 6 0
## length.max 3 0
## age.max 4 0
## IUCN.status 6 0
Multiplle correspondance analyses on the trait matrix using Burt tables.
With three axes 48.55% of total variance mapped. Quick analyses: axe one for big fishes with intermediate growth parameters (size, trophic level, age, age maturity) versus small one with low life expectancy, low trophic level and co. Axe two and three not so clear, but help to distinguish the axe one properties.
The MCA results are used to identify group of similar traits caracteristics in the MCA space. First methods test using Hennig approach and the fpc packages, then group with the best method. Methods tested with 2 to 20 groups:
This comes from the quick reading of the Hennig paper found on ArXiv (fpc paper, the metric agregation and the cluster strategy and selection to bee data - yes bee). To select the methods and the number of cluster, differents metrics are plotted and interpreted. Two type of metrics: metrics to assess cluster homogeneity and metrics to assess cluster separation. The choice of the metrics has to be in line with the cluster objectives (here to reduce the dimension of the species number in DATRAS, according to some traits similarity). Choice of the measures link to the aim of the clustering. Some random notes taken during the reading of the Hennig’s papers:
Results :